Merge pull request #24 from robmarkcole/ISSUE19

Update for current yolov5 release YOLOv5 2022-8-30

README.md

@@ -54,7 +54,7 @@ The model inference results are returned:
 An example python script to perform inference using [requests](https://docs.python-requests.org/en/master/) is given in `tests/test_request.py`
 
 ## Run & Develop locally
-Run locally and dev:
+Run locally for dev, requirements mostly originate from [yolov5](https://github.com/ultralytics/yolov5/blob/master/requirements.txt):
 * `python3 -m venv venv`
 * `source venv/bin/activate`
 * `(venv) $ pip install -r requirements.txt`

requirements.txt

@@ -1,20 +1,15 @@
 flask
 requests
-black
-
 matplotlib>=3.2.2
 numpy>=1.18.5
-opencv-python>=4.1.2
-Pillow
+opencv-python>=4.1.1
+Pillow>=7.1.2
 PyYAML>=5.3.1
+requests>=2.23.0
 scipy>=1.4.1
 torch>=1.7.0
 torchvision>=0.8.1
-tqdm>=4.41.0
-
-tensorboard>=2.4.1
-
+tqdm>=4.64.0
 seaborn>=0.11.0
 pandas
-
-thop  # FLOPs computation
+thop>=0.1.1 

restapi.py

@@ -21,9 +21,7 @@ def predict():
     if request.files.get("image"):
         image_file = request.files["image"]
         image_bytes = image_file.read()
-
         img = Image.open(io.BytesIO(image_bytes))
-
         results = model(img, size=640)
         data = results.pandas().xyxy[0].to_json(orient="records")
         return data
@@ -34,8 +32,6 @@ def predict():
     parser.add_argument("--port", default=5000, type=int, help="port number")
     args = parser.parse_args()
 
-    model = torch.hub.load(
-        "ultralytics/yolov5", "yolov5s", pretrained=True, force_reload=True
-    ).autoshape()  # force_reload = recache latest code
+    model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)  # force_reload = recache latest code
     model.eval()
     app.run(host="0.0.0.0", port=args.port)  # debug=True causes Restarting with stat

webapp.py

@@ -24,16 +24,10 @@ def predict():
 
         img_bytes = file.read()
         img = Image.open(io.BytesIO(img_bytes))
-        results = model(img, size=640)
-
-        # for debugging
-        # data = results.pandas().xyxy[0].to_json(orient="records")
-        # return data
+        results = model([img])
 
         results.render()  # updates results.imgs with boxes and labels
-        for img in results.imgs:
-            img_base64 = Image.fromarray(img)
-            img_base64.save("static/image0.jpg", format="JPEG")
+        results.save(save_dir="static/")
         return redirect("static/image0.jpg")
 
     return render_template("index.html")
@@ -44,8 +38,6 @@ def predict():
     parser.add_argument("--port", default=5000, type=int, help="port number")
     args = parser.parse_args()
 
-    model = torch.hub.load(
-        "ultralytics/yolov5", "yolov5s", pretrained=True, force_reload=True, autoshape=True
-    )  # force_reload = recache latest code
+    model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)  # force_reload = recache latest code
     model.eval()
     app.run(host="0.0.0.0", port=args.port)  # debug=True causes Restarting with stat